양자 기술 시장(2026-2046년)

The global quantum technology market entered 2026 from a position of unprecedented commercial momentum. Full-year 2025 closed with nearly $10 billion in total quantum financings - a structural acceleration rather than a hype cycle, encompassing private equity rounds, public market offerings, strategic acquisitions, and government-backed joint ventures. Q1 2025 alone delivered over $1.25 billion in equity funding, a 125% increase year-on-year, and momentum compounded through every subsequent quarter. Fifteen companies raised more than $100 million each in 2025, with average late-stage round sizes expanding from approximately $50 million in 2023 to comfortably above $100 million in 2025 - reflecting the transition from seed-stage research bets to serious commercial deployment capital.

The headline transactions reset valuation expectations across the industry. PsiQuantum closed a $1 billion Series E led by BlackRock, Temasek, and Baillie Gifford at a $7 billion post-money valuation - the largest quantum venture round in history. Quantinuum raised $600 million at a $10 billion pre-money valuation, the highest-ever for a privately held quantum company, with NVIDIA, Fidelity, and Quanta Computer participating. IQM Quantum Computers raised over $300 million in Series B funding, achieving unicorn status. IonQ executed approximately $2.5 billion in acquisitions across 18 months, absorbing Oxford Ionics ($1.075 billion), ID Quantique, and Vector Atomic to become the world's most comprehensive quantum technology platform. D-Wave's $550 million acquisition of Quantum Circuits Inc. similarly reflected industry-wide consolidation toward integrated quantum stacks.

Funding momentum has carried directly into 2026. IQM Quantum Computers announced a SPAC merger at a $1.8 billion valuation, becoming the first European quantum computing company listed on a US exchange. Xanadu Quantum Technologies advanced toward its NASDAQ listing with approximately $455 million in net cash on close. Quantinuum is pursuing a traditional underwritten IPO. The quantum sector has crossed decisively from private to public capital markets - and pricing pressure has not abated, with private and public valuations sustaining levels that would have been considered extraordinary even two years earlier.

The strategic picture for 2026 is unambiguous: capital concentration at scale, full-stack consolidation as the dominant industry strategy, photonics emerging as the scale-up architecture of choice (three of the five largest 2025 raises were photonic companies), software and control layers attracting durable platform-level investment, and quantum-AI convergence forming a genuine investment theme. Quantum technology now sits alongside AI, biotech, and advanced semiconductors as one of the defining technology investment categories of the decade.

The Global Quantum Technology Market 2026–2046: Computing, Sensors, Communications & Software is the most comprehensive market intelligence resource available on the second quantum revolution. Spanning a 20-year forecast horizon and 14 chapters, the report covers every commercially active layer of the quantum technology stack - from foundational materials and cryogenic infrastructure through QPU hardware, software platforms, sensors, communications systems, and end-use applications - with detailed market sizing, vendor analysis, and forward-looking strategic intelligence.

Report contents include:

• Executive summary including 2025 investment landscape ($10 billion in financings), Q1–Q4 quarterly funding analysis, government initiatives across 10 leading nations, supply chain concentration and geopolitical exposure, top ten supply chain bottlenecks, SWOT analysis, market map, value chain, and 2026–2046 forecasts.
• Introduction to first and second quantum revolutions, quantum mechanics principles (superposition, entanglement, coherence, tunnelling), enabling technologies, and standards development.
• Quantum computing across all eight major qubit modalities - superconducting, trapped ion, silicon spin, topological, photonic, neutral atom, diamond-defect, and quantum annealers - with technology descriptions, market players, SWOT analyses, hardware roadmaps, and detailed coverage of error correction, fault tolerance, infrastructure requirements, software, business models, and quantum-classical data centre integration.
• Quantum chemistry and AI, quantum machine learning (including QML phases, algorithms, and applications), and quantum simulation (analog vs digital approaches, simulation platforms, and chemistry applications).
• Quantum communications including QRNG, QKD (BB84, CV-QKD, DV-QKD, MDI-QKD, TF-QKD protocols), post-quantum cryptography (NIST standardisation, migration implications, market players), quantum networks, quantum memory, and quantum internet.
• Quantum sensors across atomic clocks, magnetic field sensors (SQUIDs, OPMs, TMRs, NV centres), gravimeters, gyroscopes, image sensors, radar, navigation, chemical sensors, RF field sensors (Rydberg and NV-centre based), and quantum NEMs/MEMs.
• Quantum batteries, including technology types, applications, and market forecasts.
• End-use markets spanning pharmaceuticals, financial services, aerospace and defence, energy and utilities, healthcare and medical, telecommunications, and government applications.
• Materials for quantum technologies including superconductors, photonics, nanomaterials, artificial diamond, cryogenic infrastructure, helium-3 supply chain, cryo-CMOS, lasers, UHV systems, and microwave/optical interconnects.
• Regional analysis for North America, Europe, Asia-Pacific, and Rest of World, plus government initiatives comparison.
• Global market analysis including consolidated forecasts to 2046 by segment, end-use industry, and region; supply chain market sizing; and combined quantum technology economy view.
• Profiles of 327 companies spanning every layer of the quantum technology ecosystem. Companies profiled include A* Quantum, AbaQus, Absolut System, Adaptive Finance Technologies, Aegiq, Agnostiq, Algorithmiq, Airbus, Alea Quantum, Alpine Quantum Technologies (AQT), Alice & Bob, Aliro Quantum, Anametric, Anyon Systems, Aqarios, Aquark Technologies, Archer Materials, Arclight Quantum, Arctic Instruments, Arqit Quantum, ARQUE Systems, Artificial Brain, Artilux, Atlantic Quantum, Atom Computing, Atom Quantum Labs, Atomionics, Atos Quantum, Baidu, BEIT, Beyond Blood Diagnostics, Bifrost Electronics, Bleximo, Bluefors, BlueQubit, Bohr Quantum Technology, Bosch Quantum Sensing, BosonQ Ps, C12 Quantum Electronics, Cambridge Quantum Computing (CQC), CAS Cold Atom, Cerca Magnetics, CEW Systems Canada, Chipiron, Chiral Nano, Classiq Technologies, ColibriTD, Commutator Studios, Covesion, Crypta Labs, CryptoNext Security, Crystal Quantum Computing, D-Wave Systems, DeteQt, Digistain, Diatope, Dirac, Diraq, Delft Circuits, Delta g, Duality Quantum Photonics, EeroQ, eleQtron, Element Six, Elyah, Entropica Labs, Ephos, Equal1, EuQlid, evolutionQ, Exail Quantum Sensors, EYL, First Quantum, Fujitsu, Genesis Quantum Technology, GenMat, Good Chemistry, Google Quantum AI, Groove Quantum, g2-Zero, Haiqu, Hefei Wanzheng Quantum Technology, High Q Technologies, Horizon Quantum Computing and more....

TABLE OF CONTENTS

1 EXECUTIVE SUMMARY

• 1.1 Quantum Technologies Market in 2026
  • 1.1.1 Q1 2025: The Surge That Set the Tone
  • 1.1.2 Q2 2025: Momentum Builds Across the Stack
  • 1.1.3 Q3 2025: Mega-Rounds and a New Valuation Era
  • 1.1.4 Q4 2025: Going Public and Consolidation Accelerates
  • 1.1.5 Into 2026: The Public Market Era Begins
  • 1.1.6 The Strategic Picture: What $10 Billion Means
  • 1.1.7 2025 as Quantum Technology's Commercial Watershed
• 1.2 First and second quantum revolutions
• 1.3 Current quantum technology market landscape
  • 1.3.1 Key developments
• 1.4 Technology Readiness Assessment
• 1.5 Quantum Technologies Investment Landscape
  • 1.5.1 Total market investments 2012-2026
  • 1.5.2 By Technology
  • 1.5.3 By Company
  • 1.5.4 By Application
  • 1.5.5 By Region
    • 1.5.5.1 The Quantum Market in North America
    • 1.5.5.2 The Quantum Market in Asia
    • 1.5.5.3 The Quantum Market in Europe
  • 1.5.6 Key Investment Trends 2025–2026
• 1.6 Global government initiatives and funding
  • 1.6.1 United States
  • 1.6.2 China
  • 1.6.3 European Union
  • 1.6.4 Germany
  • 1.6.5 United Kingdom
  • 1.6.6 France
  • 1.6.7 Canada
  • 1.6.8 Australia
  • 1.6.9 Japan
  • 1.6.10 India
  • 1.6.11 Cross-Cutting Themes in Government Quantum Investment
  • 1.6.12 Supply Chain Concentration and Geopolitical Exposure
• 1.7 Challenges for quantum technologies adoption
• 1.8 Critical Supply Chain Bottlenecks
• 1.9 Quantum Technology Market Map
• 1.10 SWOT Analysis
• 1.11 Quantum Technology Value Chain
• 1.12 Global Market Forecast 2026–2046
  • 1.12.1 Total Market Revenues
  • 1.12.2 By Technology Segment
  • 1.12.3 By End-Use Industry
  • 1.12.4 By Region

2 INTRODUCTION TO QUANTUM TECHNOLOGY

• 2.1 First and Second Quantum Revolutions
• 2.2 Quantum Mechanics Principles
  • 2.2.1 Superposition
  • 2.2.2 Entanglement
  • 2.2.3 Quantum Coherence
  • 2.2.4 Quantum Tunnelling
• 2.3 The Quantum Technology Ecosystem
• 2.4 Enabling Technologies and Infrastructure
• 2.5 Standards Development

3 QUANTUM COMPUTING

• 3.1 What is quantum computing?
  • 3.1.1 Operating principle
  • 3.1.2 Classical vs quantum computing
  • 3.1.3 Quantum computing technology
    • 3.1.3.1 Quantum emulators
    • 3.1.3.2 Quantum inspired computing
    • 3.1.3.3 Quantum annealing computers
    • 3.1.3.4 Quantum simulators
    • 3.1.3.5 Digital quantum computers
    • 3.1.3.6 Continuous variables quantum computers
    • 3.1.3.7 Measurement Based Quantum Computing (MBQC)
    • 3.1.3.8 Topological quantum computing
    • 3.1.3.9 Quantum Accelerator
• 3.2 Benchmarking and Performance Metrics
  • 3.2.1 Qubit Count
  • 3.2.2 Gate Fidelity
  • 3.2.3 Coherence Times
  • 3.2.4 Quantum Volume
  • 3.2.5 Competition from other technologies
  • 3.2.6 Quantum algorithms
    • 3.2.6.1 Quantum Software Stack
    • 3.2.6.2 Quantum Machine Learning
    • 3.2.6.3 Quantum Simulation
    • 3.2.6.4 Quantum Optimization
    • 3.2.6.5 Quantum Cryptography
      • 3.2.6.5.1 Quantum Key Distribution (QKD)
      • 3.2.6.5.2 Post-Quantum Cryptography
  • 3.2.7 Architectural Approaches
    • 3.2.7.1 Modular vs. Single Core
    • 3.2.7.2 Heterogeneous Multi-Qubit Architectures
  • 3.2.8 Hardware
    • 3.2.8.1 Qubit Technologies
      • 3.2.8.1.1 Superconducting Qubits
        • 3.2.8.1.1.1 Technology description
        • 3.2.8.1.1.2 Materials
        • 3.2.8.1.1.3 Hardware Architecture
        • 3.2.8.2.1.4 Market players
        • 3.2.8.2.1.5 Swot analysis
        • 3.2.8.2.1.6 Superconducting Hardware Roadmap
      • 3.2.8.1.2 Trapped Ion Qubits
        • 3.2.8.2.2.1 Technology description
        • 3.2.8.2.2.2 Ion Species Comparison
        • 3.2.8.2.2.3 Trap Architectures
        • 3.2.8.2.2.4 Materials
          • 3.2.8.2.2.4.1 Integrating optical components
          • 3.2.8.2.2.4.2 Incorporating high-quality mirrors and optical cavities
          • 3.2.8.2.2.4.3 Engineering the vacuum packaging and encapsulation
          • 3.2.8.2.2.4.4 Removal of waste heat
        • 3.2.8.2.2.5 Market players
        • 3.2.8.2.2.6 Swot analysis
        • 3.2.8.2.2.7 Trapped Ion Hardware Roadmap
      • 3.2.8.2.3 Silicon Spin Qubits
        • 3.2.8.2.3.1 Technology description
        • 3.2.8.2.3.2 Quantum dots
        • 3.2.8.2.3.3 Market players
        • 3.2.8.2.3.4 SWOT analysis
        • 3.2.8.2.3.5 Silicon Spin Hardware Roadmap
      • 3.2.8.2.4 Topological Qubits
        • 3.2.8.2.4.1 Technology description
          • 3.2.8.2.4.1.1 Cryogenic cooling
        • 3.2.8.2.4.2 Market players
        • 3.2.8.2.4.3 SWOT analysis
      • 3.2.8.2.5 Photonic Qubits
        • 3.2.8.2.5.1 Technology description
          • 3.2.8.2.5.1.1 Architectural Classes
          • 3.2.8.2.5.1.2 Initialization, Manipulation, and Readout
          • 3.2.8.2.5.1.3 Hardware Architecture
        • 3.2.8.2.5.2 Race to Photonic Fault Tolerance: Tier Analysis
        • 3.2.8.2.5.3 Market players
        • 3.2.8.2.5.4 Swot analysis
        • 3.2.8.2.5.5 Photonic Hardware Roadmap
        • 3.2.8.2.5.6 Race to Photonic Fault Tolerance: Tier Analysis
      • 3.2.8.2.6 Neutral atom (cold atom) qubits
        • 3.2.8.2.6.1 Technology description
        • 3.2.8.2.6.2 Market players
        • 3.2.8.2.6.3 Swot analysis
        • 3.2.8.2.6.4 Neutral Atom Hardware Roadmap
      • 3.2.8.2.7 Diamond-defect qubits
        • 3.2.8.2.7.1 Technology description
        • 3.2.8.2.7.2 SWOT analysis
        • 3.2.8.2.7.3 Market players
        • 3.2.8.2.7.4 Diamond-Defect Hardware Roadmap
      • 3.2.8.2.8 Quantum annealers
        • 3.2.8.2.8.1 Technology description
        • 3.2.8.2.8.2 SWOT analysis
        • 3.2.8.2.8.3 Market players
        • 3.2.8.2.8.4 Quantum Annealing Hardware Roadmap
    • 3.2.8.3 Architectural Approaches
    • 3.2.8.4 Quantum Computing Infrastructure Requirements
  • 3.2.9 Software
    • 3.2.9.1 Technology description
    • 3.2.9.2 Cloud-based services- QCaaS (Quantum Computing as a Service).
      • 3.2.9.2.1 The Cloud-First Reality of Quantum Computing
      • 3.2.9.2.2 Platform Architecture Models
      • 3.2.9.2.3 Major Quantum Cloud Platforms
      • 3.2.9.2.4 Pricing Models
      • 3.2.9.2.5 Quantum Cloud Platform Comparison
      • 3.2.9.2.6 Cloud Platform Market Forecast
    • 3.2.9.3 Market players
• 3.3 Market challenges
• 3.4 SWOT analysis
• 3.5 Business Models
• 3.6 Quantum Error Correction and Fault Tolerance
  • 3.6.1 Why Error Correction Matters
  • 3.6.2 Quantum Error Correction Code Families
  • 3.6.3 Fault Tolerance Requirements and Logical Qubit Demonstrations
  • 3.6.4 Magic State Distillation and Logical Gate Sets
  • 3.6.5 Hardware-Aware Error Correction
  • 3.6.6 QEC-Specific Vendors and Software Stack
  • 3.6.7 Resource Estimation for Fault-Tolerant Algorithms
  • 3.6.8 Market Forecast — QEC-Related Spending
• 3.7 Quantum Computing in Data Centres
  • 3.7.1 Overview
  • 3.7.2 Photonic Deployment Models in Data Centres
• 3.8 Quantum computing value chain
• 3.9 Markets and applications for quantum computing
  • 3.9.1 Pharmaceuticals
    • 3.9.1.1 Market overview
      • 3.9.1.1.1 Drug discovery
      • 3.9.1.1.2 Diagnostics
      • 3.9.1.1.3 Molecular simulations
      • 3.9.1.1.4 Genomics
      • 3.9.1.1.5 Proteins and RNA folding
    • 3.9.1.2 Market players
  • 3.9.2 Chemicals
    • 3.9.2.1 Market overview
    • 3.9.2.2 Market players
  • 3.9.3 Transportation
    • 3.9.3.1 Market overview
    • 3.9.3.2 Market players
  • 3.9.4 Financial services
    • 3.9.4.1 Market overview
    • 3.9.4.2 Market players
• 3.10 Opportunity analysis
• 3.11 Technology roadmap
• 3.12 Quantum-Inspired Classical Computing
  • 3.12.1 What is Quantum-Inspired Computing?
  • 3.12.2 Quantum-Inspired Algorithms
  • 3.12.3 Quantum-Inspired Hardware Architectures
  • 3.12.4 Commercial Applications
  • 3.12.5 Major Quantum-Inspired Vendors
  • 3.12.6 Quantum vs Quantum-Inspired: Strategic Positioning
  • 3.12.7 Market Forecast — Quantum-Inspired Computing

4 QUANTUM CHEMISTRY AND ARTIFICAL INTELLIGENCE (AI)

• 4.1 Technology description
• 4.2 Applications
• 4.3 SWOT analysis
• 4.4 Market challenges
• 4.5 Market players
• 4.6 Opportunity analysis
• 4.7 Technology roadmap

5 QUANTUM MACHINE LEARNING

• 5.1 What is Quantum Machine Learning?
• 5.2 Classical vs. Quantum Computing Paradigms for ML
• 5.3 Quantum Mechanical Principles for ML
• 5.4 Machine Learning Fundamentals
• 5.5 The Intersection — Why Combine Quantum and ML?
• 5.6 QML Phases and Evolution
  • 5.6.1 The First Phase of QML
  • 5.6.2 The Second Phase of QML
• 5.7 Algorithms and Software for QML
• 5.8 Quantum Neural Networks
• 5.9 Variational Quantum Classifiers
• 5.10 Quantum Kernel Methods
• 5.11 Advantages of QML
  • 5.11.1 Improved Optimisation and Generalisation
  • 5.11.2 Quantum Advantage in ML
  • 5.11.3 Training Advantages and Opportunities
  • 5.11.4 Improved Accuracy
• 5.12 Challenges and Limitations
  • 5.12.1 Hardware Constraints
  • 5.12.2 Costs
  • 5.12.3 Nascent Technology
• 5.13 QML Applications
• 5.14 QML Roadmap
• 5.15 Market Players
• 5.16 Market Forecasts 2026–2036

6 QUANTUM SIMULATION

• 6.1 What is Quantum Simulation?
• 6.2 Analog vs. Digital Quantum Simulation
• 6.3 Quantum Simulation Platforms
  • 6.3.1 Neutral Atom Simulators
  • 6.3.2 Trapped Ion Simulators
  • 6.3.3 Superconducting Circuit Simulators
  • 6.3.4 Photonic Simulators
• 6.4 Applications of Quantum Simulation
  • 6.4.1 Molecular and Chemical Simulation
  • 6.4.2 Materials Discovery
  • 6.4.3 High-Energy Physics
  • 6.4.4 Condensed Matter Physics
  • 6.4.5 Drug Discovery and Protein Folding
• 6.5 Quantum Chemistry Simulation
• 6.6 Market Players
• 6.7 SWOT Analysis
• 6.8 Market Forecasts 2026–2036

7 QUANTUM COMMUNICATIONS

• 7.1 Technology description
• 7.2 Types
• 7.3 Applications
• 7.4 Quantum Random Numbers Generators (QRNG)
  • 7.4.1 Overview
  • 7.4.2 QRNG Product Design and Technology Evolution
  • 7.4.3 Entropy Sources
  • 7.4.4 High Throughput as Key Differentiator
  • 7.4.5 Standards Development
  • 7.4.6 Applications
    • 7.4.6.1 Encryption for Data Centers
    • 7.4.6.2 Consumer Electronics
    • 7.4.6.3 Automotive/Connected Vehicle
    • 7.4.6.4 Gambling and Gaming
    • 7.4.6.5 Monte Carlo Simulations
    • 7.4.6.6 Government and Defense Applications
    • 7.4.6.7 Enterprise Networks and Data Centers
    • 7.4.6.8 Automotive Applications
    • 7.4.6.9 Online Gaming
  • 7.4.7 Advantages
  • 7.4.8 Principle of Operation of Optical QRNG Technology
  • 7.4.9 Non-optical approaches to QRNG technology
  • 7.4.10 SWOT Analysis
  • 7.4.11 Market Forecasts
• 7.5 Quantum Key Distribution (QKD)
  • 7.5.1 Overview
  • 7.5.2 Asymmetric and Symmetric Keys
  • 7.5.3 Principle behind QKD
  • 7.5.4 Why is QKD More Secure Than Other Key Exchange Mechanisms?
  • 7.5.5 Discrete Variable vs. Continuous Variable QKD Protocols
  • 7.5.6 MDI-QKD (Measurement Device Independent QKD)
  • 7.5.7 Fiber-Based QKD
  • 7.5.8 Free-Space and Satellite QKD
  • 7.5.9 Key Players
  • 7.5.10 Challenges
  • 7.5.11 SWOT Analysis
  • 7.5.12 Market Forecasts
• 7.6 Post-quantum cryptography (PQC)
  • 7.6.1 Overview
  • 7.6.2 Security systems integration
  • 7.6.3 PQC standardization
    • 7.6.3.1 NIST Standardisation Process and Outcomes
    • 7.6.3.2 Migration Implications
  • 7.6.4 Transitioning cryptographic systems to PQC
  • 7.6.5 Market players
  • 7.6.6 SWOT Analysis
  • 7.6.7 Market Forecasts
    • 7.6.7.1 Beyond Algorithms: The Migration Reality
    • 7.6.7.2 The Migration Stack
    • 7.6.7.3 Industry-Specific Migration Programs
    • 7.6.7.4 Migration Services and Consulting Market
    • 7.6.7.5 Market Forecast — Quantum-Safe Migration
    • 7.6.7.6 Y2Q Timeline and Strategic Implications
• 7.7 Quantum homomorphic cryptography
• 7.8 Quantum Teleportation
• 7.9 Quantum Networks
  • 7.9.1 Overview
  • 7.9.2 Advantages
  • 7.9.3 Role of Trusted Nodes and Trusted Relays
  • 7.9.4 Entanglement Swapping and Optical Switches
  • 7.9.5 Multiplexing quantum signals with classical channels in the O-band
    • 7.9.5.1 Wavelength-division multiplexing (WDM) and time-division multiplexing (TDM)
  • 7.9.6 Twin-Field Quantum Key Distribution (TF-QKD)
  • 7.9.7 Enabling global-scale quantum communication
  • 7.9.8 Advanced optical fibers and interconnects
  • 7.9.9 Photodetectors in quantum networks
    • 7.9.9.1 Avalanche photodetectors (APDs)
    • 7.9.9.2 Single-photon avalanche diodes (SPADs)
    • 7.9.9.3 Silicon Photomultipliers (SiPMs)
  • 7.9.10 Cryostats
    • 7.9.10.1 Cryostat architectures
  • 7.9.11 Infrastructure requirements
  • 7.9.12 Global activity
    • 7.9.12.1 China
    • 7.9.12.2 Europe
    • 7.9.12.3 The Netherlands
    • 7.9.12.4 The United Kingdom
    • 7.9.12.5 US
    • 7.9.12.6 Japan
  • 7.9.13 SWOT analysis
• 7.10 Quantum Memory
• 7.11 Quantum Internet
• 7.12 Global Market for Quantum Communications by Technology Type 2026–2036
• 7.13 Market challenges
• 7.14 Market players
• 7.15 Opportunity analysis
• 7.16 Technology roadmap

8 QUANTUM SENSORS

• 8.1 Technology description
  • 8.1.1 Quantum Sensing Principles
  • 8.1.2 SWOT analysis
  • 8.1.3 Atomic Clocks
    • 8.1.3.1 High frequency oscillators
      • 8.1.3.1.1 Emerging oscillators
    • 8.1.3.2 Caesium atoms
    • 8.1.3.3 Self-calibration
    • 8.1.3.4 Optical atomic clocks
      • 8.1.3.4.1 Chip-scale optical clocks
    • 8.1.3.5 Bench/Rack-Scale Atomic Clocks
    • 8.1.3.6 Chip-Scale Atomic Clocks (CSAC)
    • 8.1.3.7 Atomic Clocks Market Forecasts — Total
    • 8.1.3.8 Companies
    • 8.1.3.9 SWOT analysis
  • 8.1.4 Quantum Magnetic Field Sensors
    • 8.1.4.1 Introduction
    • 8.1.4.2 Motivation for use
    • 8.1.4.3 Market opportunity
    • 8.1.4.4 Superconducting Quantum Interference Devices (Squids)
      • 8.1.4.4.1 Applications
      • 8.1.4.4.2 Key players
      • 8.1.4.4.3 SWOT analysis
    • 8.1.4.5 Optically Pumped Magnetometers (OPMs)
      • 8.1.4.5.1 Applications
      • 8.1.4.5.2 Key players
      • 8.1.4.5.3 SWOT analysis
    • 8.1.4.6 Tunneling Magneto Resistance Sensors (TMRs)
      • 8.1.4.6.1 Applications
      • 8.1.4.6.2 Key players
      • 8.1.4.6.3 SWOT analysis
    • 8.1.4.7 Nitrogen Vacancy Centers (N-V Centers)
      • 8.1.4.7.1 Applications
      • 8.1.4.7.2 Key players
      • 8.1.4.7.3 SWOT analysis
  • 8.1.5 Quantum Gravimeters
    • 8.1.5.1 Technology description
    • 8.1.5.2 Applications
    • 8.1.5.3 Key players
    • 8.1.5.4 SWOT analysis
  • 8.1.6 Quantum Gyroscopes
    • 8.1.6.1 Technology description
      • 8.1.6.1.1 Inertial Measurement Units (IMUs)
      • 8.1.6.1.2 Atomic quantum gyroscopes
    • 8.1.6.2 Applications
    • 8.1.6.3 Key players
    • 8.1.6.4 SWOT analysis
  • 8.1.7 Quantum Image Sensors
    • 8.1.7.1 Technology description
    • 8.1.7.2 Applications
    • 8.1.7.3 SWOT analysis
    • 8.1.7.4 Key players
  • 8.1.8 Quantum Radar
    • 8.1.8.1 Technology description
    • 8.1.8.2 Applications
  • 8.1.9 Quantum Navigation
  • 8.1.10 Quantum Sensor Components
  • 8.1.11 Quantum Chemical Sensors
    • 8.1.11.1 Technology overview
    • 8.1.11.2 Commercial activities
  • 8.1.12 Quantum Radio Frequency Field Sensors
    • 8.1.12.1 Overview
    • 8.1.12.2 Rydberg Atom Based Electric Field Sensors and Radio Receivers
      • 8.1.12.2.1 Principles
      • 8.1.12.2.2 Commercialization
    • 8.1.12.3 Nitrogen-Vacancy Centre Diamond Electric Field Sensors and Radio Receivers
      • 8.1.12.3.1 Principles
      • 8.1.12.3.2 Applications
    • 8.1.12.4 Market
  • 8.1.13 Quantum NEM and MEMs
    • 8.1.13.1 Technology description
• 8.2 Market and technology challenges
• 8.3 Market forecasts
  • 8.3.1 By Sensor Type
  • 8.3.2 By Volume
  • 8.3.3 By Sensor Price
  • 8.3.4 By End-Use Industry
• 8.4 Technology roadmap

9 QUANTUM BATTERIES

• 9.1 Technology description
• 9.2 Types
• 9.3 Applications
• 9.4 SWOT analysis
• 9.5 Market challenges
• 9.6 Market players
• 9.7 Opportunity analysis
• 9.8 Technology roadmap

10 END-USE MARKETS AND APPLICATIONS

• 10.1 Overview
• 10.2 Pharmaceuticals and Drug Discovery
  • 10.2.1 Market Overview
  • 10.2.2 Drug Discovery Applications
• 10.3 Financial Services
  • 10.3.1 Market Overview
  • 10.3.2 Portfolio Optimisation
  • 10.3.3 Risk Assessment
  • 10.3.4 Algorithmic Trading
  • 10.3.5 Fraud Detection
• 10.4 Aerospace and Defence
  • 10.4.1 Market Overview
  • 10.4.2 Navigation and Positioning
  • 10.4.3 Secure Communications
  • 10.4.4 Simulation and Optimisation
• 10.5 Energy and Utilities
  • 10.5.1 Market Overview
  • 10.5.2 Grid Optimisation
  • 10.5.3 Renewable Energy Integration
  • 10.5.4 Carbon Capture Optimisation
• 10.6 Healthcare and Medical
  • 10.6.1 Market Overview
  • 10.6.2 Medical Imaging
  • 10.6.3 Diagnostics
  • 10.6.4 Personalized Medicine
• 10.7 Telecommunications
  • 10.7.1 Market Overview
  • 10.7.2 Network Optimisation
  • 10.7.3 Quantum-Secure Networks
• 10.8 Government and Public Sector
  • 10.8.1 Market Overview

11 MATERIALS FOR QUANTUM TECHNOLOGIES

• 11.1 Superconductors
  • 11.1.1 Overview
  • 11.1.2 Types and Properties
  • 11.1.3 Critical Temperature and Material Selection
    • 11.1.3.1 Critical Material Supply Chain Considerations
  • 11.1.4 Superconducting Quantum Circuits
    • 11.1.4.1 Introduction
    • 11.1.4.2 Fabricating Superconducting Qubits
  • 11.1.5 Defects and Sources of Noise
  • 11.1.6 Superconducting Nanowire Single-Photon Detectors (SNSPDs) — Materials and Fabrication
  • 11.1.7 Opportunities
• 11.2 Photonics, Silicon Photonics and Optical Components
  • 11.2.1 Overview
  • 11.2.2 Types and Properties
  • 11.2.3 Photonic Integrated Circuits for Quantum Technology
    • 11.2.3.1 Overview
  • 11.2.4 PICs for Quantum Sensing
  • 11.2.5 Opportunities
• 11.3 Nanomaterials
  • 11.3.1 Overview
  • 11.3.2 Types and Properties
  • 11.3.3 Opportunities
• 11.4 Artificial Diamond for Quantum Technology
  • 11.4.1 Overview
  • 11.4.2 Supply Chain and Materials for Diamond-Based Quantum Computers
  • 11.4.3 Quantum Grade Diamond
  • 11.4.4 Silicon-Vacancy in Diamond Quantum Memory
• 11.5 Cryogenic Infrastructure
  • 11.5.1 The Role of Cryogenics in Quantum Computing
  • 11.5.2 Operating Temperature Requirements by Modality
  • 11.5.3 Dilution Refrigerators
    • 11.5.3.1 Cryogen-Free vs. Wet Systems
      • 11.5.3.1.1.1 Modular and Cube-Format Architectures
  • 11.5.4 Pulse Tube and Cryocoolers
  • 11.5.5 Alternative Cooling Technologies
  • 11.5.6 Dilution Refrigerator Vendor Landscape
  • 11.5.7 Partnership Models
  • 11.5.8 Cryogenic System Lead Times and Capacity Constraints
  • 11.5.9 Ten-Year Forecast — Installed Base of Dilution Refrigerators
• 11.6 Helium-3 Supply Chain
  • 11.6.1 Why Helium-3 Matters for Quantum Computing
  • 11.6.2 ³He Production from Tritium Decay
  • 11.6.3 ³He Supply Sources and Annual Production Estimates
  • 11.6.4 Demand-Supply Gap Modelling, 2026–2046
  • 11.6.5 Lunar Regolith Harvesting (Interlune)
  • 11.6.6 Helium-4 Industrial Supply Risk
  • 11.6.7 Strategic Stockpiling and Mitigation
• 11.7 Cryogenic Control Electronics and Cryo-CMOS
  • 11.7.1 The Wiring Crisis — Why Room-Temperature Control Cannot Scale
  • 11.7.2 Architectural Approaches
  • 11.7.3 NVQLink and the Quantum-Classical Data Centre Convergence
  • 11.7.4 Cryo-CMOS Devices and Process Technology
  • 11.7.5 Vendor Landscape
  • 11.7.6 Cryogenic Amplifiers — TWPAs, HEMT and Parametric
  • 11.7.7 Heat Load Budgets and Power Dissipation Constraints
  • 11.7.8 Ten-Year Forecast — Cryo-CMOS Market and Penetration
• 11.8 Lasers and Photonic Components by Modality
  • 11.8.1 The Laser Bill of Materials in a Quantum System
  • 11.8.2 Wavelengths Required by Atomic and Solid-State Modalities
  • 11.8.3 Laser Technology Platforms
  • 11.8.4 Linewidth, Stability and Phase Noise Requirements
  • 11.8.5 Photonic Component Suppliers
  • 11.8.6 Laser Vendor Capability Matrix
  • 11.8.7 Single-Photon Detection
  • 11.8.8 Photonic Integrated Circuits and Foundry Access
• 11.9 Ultra-High Vacuum (UGV) Systems
  • 11.9.1 Vacuum Pressure Requirements by Modality
  • 11.9.2 UHV Chamber Design and Materials
  • 11.9.3 Vacuum Pumps and Hardware
  • 11.9.4 Vacuum Feedthroughs and Hermetic Seals
  • 11.9.5 Vapour Cell Technology and Atomic Sources
  • 11.9.6 UHV Vendor Capability Matrix
• 11.10 Microwave and Optical Interconnects
  • 11.10.1 Cryogenic Microwave Cabling
  • 11.10.2 High-Density Cryogenic Connectors
  • 11.10.3 Cryogenic Attenuators and Filters
  • 11.10.4 Circulators, Isolators and Switches
  • 11.10.5 Optical Interconnects for Photonic and Modular Quantum Systems
  • 11.10.6 Microwave-to-Optical Transducers
  • 11.10.7 Vendor Landscape
• 11.11 Supply Chain Bottleneck Assessment
  • 11.11.1 Methodology — Severity, Probability and Time-to-Resolution Framework
  • 11.11.2 Critical Bottlenecks
  • 11.11.3 High-Severity Bottlenecks
  • 11.11.4 Bottleneck Heat-Map by Modality
  • 11.11.5 Mitigation Strategies
• 11.12 Materials Market Forecasts
  • 11.12.1 Forecasting Methodology and Scenario Definitions
  • 11.12.2 Superconducting Chips and Substrates
  • 11.12.3 Photonic Integrated Circuits and Optical Components
  • 11.12.4 Cryogenic Infrastructure
  • 11.12.5 Helium-3 and Helium-4 Supply
  • 11.12.6 Cryogenic Control Electronics and Cryo-CMOS
  • 11.12.7 Lasers and Single-Photon Detectors
  • 11.12.8 Ultra-High Vacuum Systems
  • 11.12.9 Microwave and Optical Interconnects
  • 11.12.10 Diamond and Quantum Materials
  • 11.12.11 Nanomaterials for Quantum Applications
• 11.13 North America
  • 11.13.1 United States
  • 11.13.2 Canada
• 11.14 Europe
  • 11.14.1 European Union Initiatives
  • 11.14.2 United Kingdom
  • 11.14.3 Germany
  • 11.14.4 France
  • 11.14.5 Netherlands
• 11.15 Asia-Pacific
  • 11.15.1 China
  • 11.15.2 Japan
  • 11.15.3 South Korea
  • 11.15.4 Australia
  • 11.15.5 Singapore
• 11.16 Rest of World
• 11.17 Government Initiatives Comparison

12 GLOBAL MARKET ANALYSIS

• 12.1 Market map
• 12.2 Key industry players
  • 12.2.1 Start-ups
  • 12.2.2 Tech Giants
  • 12.2.3 National Initiatives
• 12.3 Global market revenues 2018-2046
  • 12.3.1 Quantum Computing
  • 12.3.2 Quantum Sensors
  • 12.3.3 QKD Systems
  • 12.3.4 Quantum Random Number Generators (QRNG)
  • 12.3.5 Post-Quantum Cryptography (PQC)
  • 12.3.6 Quantum Machine Learning
  • 12.3.7 Quantum Simulation
  • 12.3.8 Quantum Batteries
  • 12.3.9 Total Quantum TechnologyMarket — Consolidated Forecast
  • 12.3.10 Quantum Hardware Supply Chain Market
    • 12.3.10.1 Geographic Distribution of Supply Chain Revenue
  • 12.3.11 Total Quantum Technology Market Including Supply Chain
• 12.4 Quantum Workforce and Talent Market
  • 12.4.1 Why Workforce Matters
  • 12.4.2 The Quantum Talent Pyramid
  • 12.4.3 University Programs and Degrees
  • 12.4.4 Industry Training Programs
  • 12.4.5 Government Workforce Initiatives
  • 12.4.6 Compensation Benchmarks
  • 12.4.7 Workforce Market Forecast

13 COMPANY PROFILES 435 (345 company profiles)

14 RESEARCH METHODOLOGY

15 TERMS AND DEFINITIONS

16 REFERENCES